Experimental and Regression-Based Wear Analysis of MWCNT Reinforced AA7075 Using Box-Behnken Design
DOI:
https://doi.org/10.5281/zenodo.15348294Keywords:
A7075 metal matrix composite, multi-walled carbon nanotubes (MWCNTs), wear rate optimization, response surface methodology, design of experiments (DOE), regression analysisAbstract
The research analyzes the wear characteristics of MWCNT-reinforced AA7075 metal matrix composites under different combinations of MWCNT volume fraction (2–6 wt%), operating temperature (80–120°C) and applied force (40–60 N). The wear resistance of composites produced by stir-casting fabrication received analysis through ANOVA combined with regression modeling after testing their wear resistance properties. A combination of 6% reinforcement with 100°C temperature under 40 N load proved to be the optimal conditions according to the desirability function approach which led to a wear rate of 3.349 Nm/mm³ and 0.826 in desirability. The studies reveal that reinforcement percentage served as the key variable (p = 0.004) which decreased wear by 25% when using 2% MWCNTs. Performance outcomes were most significantly improved through moderation of temperature conditions at 100°C combined with loading at 40 N. A developed regression model demonstrated the capability to predict wear rates with less than 5% error accuracy following validation through experimental confirmation. The obtained results can directly help engineers build high-wear-resistant composites for industries focused on aerospace and automotive manufacturing.
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Suresh, S., Sudhakara, D., & Vinod, B. (2020). Investigation on mechanical, wear, and machining characteristics of Al 7075/MWCNTs using the liquid state method. Advanced Composites and Hybrid Materials, 3, 243-254. https://doi.org/10.1007/s42114-020-00156-2.
Jain, A., Kumar, C. S., & Shrivastava, Y. (2023). An effort for identifying suitable machining range during drilling of a novel Al-based composite using electric discharge machine. Int. J. Exp. Res. Rev., 36, 327-346. https://doi.org/10.52756/ijerr.2023.v36.030.
Sanju, M., Saravanan, M., Krishna, G., & Kumaran, S. (2020). An investigation of wear behavior on AA7075 MMC reinforced with CNT and fly ash composites. Materials Today: Proceedings, 22, 2460-2468. https://doi.org/10.1016/j.matpr.2020.03.373.
Abedalrhman, K. . (2024). Integrative analysis of FinTech innovations in industry: Enhancements and challenges. International Journal of Engineering and Management Research, 14(5), 31–37. https://doi.org/10.5281/zenodo.13937989.
Chaturvedi, R., Sharma, A., Sharma, K., & Saraswat, M. (2022). Tribological behaviour of multi-walled carbon nanotubes reinforced AA 7075 nano-composites. Advances in Materials and Processing Technologies, 8, 4743-4755. https://doi.org/10.1080/2374068X.2022.2080330.
Saoudi, M., Ajjel, R., & Zaidi, B. (2017). Recent progress in organic nano-composites: Synthesis and treatments for use as active layers in electronic devices. Int. J. Exp. Res. Rev., 9, 11-46. Retrieved from https://qtanalytics.in/journals/index.php/IJERR/article/view/1301.
Selvaraj, S., Srinivasan, K., S, R., & Hu, Y. (2020). Sensor-assisted assessment of the tribological behavior patterns of AA7075 hybrid MMC reinforced with multi-wall carbon nanotubes and pulverized fuel ash. Materials, 13. https://doi.org/10.3390/ma13112583.
Gecu, R., Yurekturk, Y., Tekoğlu, E., Muhaffel, F., & Karaaslan, A. (2019). Improving wear resistance of 304 stainless steel reinforced AA7075 aluminum matrix composite by micro-arc oxidation. Surface and Coatings Technology. https://doi.org/10.1016/J.SURFCOAT.2019.04.029.
Pasha, S., P, R., & P, L. (2017). Wear behavior and Microstructural Characterization of AA7075/MWCNT Surface Composites fabricated through Friction Stir Processing. IOSR Journal of Mechanical and Civil Engineering, 14, 140-146. https://doi.org/10.9790/1684-140305140146.
Murugabalaji, V., Rout, M., & Sahoo, B. (2024). Wear behaviour analysis of thermo-mechanically processed AA7075 and AA7075/SiC/Graphite composite. Materials Chemistry and Physics. https://doi.org/10.1016/j.matchemphys.2024.129890.
Feijoo, I., Pena, G., Cabeza, M., Cristóbal, M., & Rey, P. (2021). MWCNT-reinforced AA7075 Composites: Effect of reinforcement percentage on mechanical properties. Metals. https://doi.org/10.3390/met11060969.
Kaur, N., Singh, K., & Garg, V. (2023). Modelling, sensitivity analysis and optimization of system parameters of edible oil refinery. Int. J. Exp. Res. Rev., 35, 25-33. https://doi.org/10.52756/ijerr.2023.v35spl.003.
Chaturvedi, R., Sharma, A., Sharma, K., & Saraswat, M. (2022). Tribological behaviour of multi-walled carbon nanotubes reinforced AA 7075 nano-composites. Advances in Materials and Processing Technologies, 8, 4743 - 4755. https://doi.org/10.1080/2374068X.2022.2080330.
Murugabalaji, V., Rout, M., & Sahoo, B. (2024). Wear behaviour analysis of thermo-mechanically processed AA7075 and AA7075/SiC/Graphite composite. Materials Chemistry and Physics. https://doi.org/10.1016/j.matchemphys.2024.129890.
Manubolu, V., & Vanimireddy, D. (2023). Experimental study on mechanical behaviour of arhar-reinforced composites using GRA with PCA. Int. J. Exp. Res. Rev., 36, 232-243. https://doi.org/10.52756/ijerr.2023.v36.023.
Pawan D. Somavanshi,, & Yogesh U. Sathe. (2025). Exploring the synthesis processes of graphene oxide and silicon dioxide nanospheres: A comprehensive study. Journal of the Textile Association (JTA) 85(4), 1–7. https://doi.org/10.5281/zenodo.14608400.
Kumar, J., & Smart, D. (2022). Study on mechanical and wear behaviour of AA7075/TaC/Si3N4/Ti hybrid metal matrix composites. International Journal of Surface Engineering and Interdisciplinary Materials Science. https://doi.org/10.4018/ijseims.2022010105.
Kumar, P., & Mashinini, P. (2020). Dry sliding wear behaviour of AA7075 – Al2SiO5 layered nanoparticle material at different temperature condition. Silicon. https://doi.org/10.1007/s12633-020-00728-3.
Nikalje, A. M., & Somavanshi, P. (2020). CNC turning parameter optimization for MRR of SS 430 using taguchi methodology. International Research Journal of Engineering and Technology (IRJET), 7(9), 1200.
Shikabonga, J., Lungu, K. A., Mwaba, D., Mubita, C., Mulenga, M. N., & Mwanaumo, E. (2025). Sustainable construction: Optimization of microbial soil stabilization for enhanced construction materials. International Journal of Engineering and Management Research, 15(1), 36–52. https://doi.org/10.5281/zenodo.14874393.
Dsouza, S., Gowda, M. S., Naik, A. S., Ankolekar, N., & Dsouza, S. W. (2024). Multiple rice leaf disease prediction for MO4 rice leaf variety in dakshina kannada using deep learning technique. International Journal of Engineering and Management Research, 14(6), 68–70. https://doi.org/10.31033/ijemr.14.6.68-70.
Naeema Nazar, Aeliswa Raju, Alex Benny, & Ranjeesh R Chandran. (2024). Carbon footprint and sustainability: Assessment and optimization in urban development. International Journal of Engineering and Management Research, 14(5), 38–42. https://doi.org/10.5281/zenodo.13950060.
Banerjee, A. (2020). Wavelength dependent photosensitivity modulation of Aluminium/Lead sulphide/Indium tin oxide back-to-back diode. Int. J. Exp. Res. Rev., 22, 1-7. https://doi.org/10.52756/ijerr.2020.v22.001.
Pawan D. Somavanshi, & Yogesh U. Sathe. (2023). Evaluating the electrochemical performance of graphite and silicon-based materials in energy storage device. Revista Electronica De Veterinaria, 24(4), 474-479. https://doi.org/10.69980/redvet.v24i4.1277.
Biswas, B., Chatterjee, S., & Chabri, S. (2016). Study on the effect of aluminium addition on the physical properties of unsaturated polyester/ jute composites. Int. J. Exp. Res. Rev., 2, 10-13. https://doi.org/10.52756/ijerr.2016.v2.003.
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